时间分层病例交叉研究偏倚的探讨
Insight into bias in time-stratified case-crossover studies
摘要：
病例交叉设计的使用在流行病学和短暂关联的医学研究中已变得普遍。然而，最流行的参考选择策略，时间分层模式，是不是一个合适的解决方案，控制偏倚的病例交叉研究。为了证明这一点，我们进行了时间序列分解每日臭氧（O3）的记录;审查的能力的时间分层模式控制的年度，月度和每周的时间趋势;并发现它未能控制每周的时间趋势。基于这一发现，我们提出了一种新的逻辑斯谛回归方法，在该方法中，我们对每周的时间趋势进行了调整。通过仿真比较了传统模型和所提出的方法。进行了一项实证研究，以探讨空气污染物和急性心肌梗死住院之间的潜在联系。总之，时间分层模式提供了有效的控制每年和每月的时间趋势，但不是每周的时间趋势。因此，从传统的逻辑回归估计基本上揭示了每周的时间趋势的影响，而不是瞬态效应。相比之下，建议的逻辑斯谛回归调整每周的时间趋势，可以有效地消除系统偏差的情况下，交叉研究。
英文摘要：
The use of case-crossover designs has become widespread in epidemiological and medical investigations of transient associations. However, the most popular reference-select strategy, the time-stratified schema, is not a suitable solution for controlling bias in case-crossover studies. To prove this, we conducted a time series decomposition for daily ozone (O3) records; scrutinized the ability of the time-stratified schema on controlling the yearly, monthly and weekly time trends; and found it failed on controlling the weekly time trend. Based on this finding, we proposed a new logistic regression approach in which we did adjustment for the weekly time trend. A comparison between the traditional model and the proposed method was done by simulation. An empirical study was conducted to explore potential associations between air pollutants and AMI hospitalizations. In summary, time-stratified schema provide effective control on yearly and monthly time trends but not on weekly time trend. Therefore, the estimation from the traditional logistical regression basically reveals the effect of weekly time trend, instead of the transient effect. In contrast, the proposed logistic regression with adjustment for weekly time trend can effectively eliminate system bias in case-crossover studies.
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